Consistently great customer service. Across every conversation.

Revelir grades every conversation your team handles, against the QA scorecard you already use.

Live in production at enterprises like Xendit Tiket.com

Revelir grades your customer service conversations the way your best QA lead would.

  • Your QA lead reads the conversation, checks it against your SOPs, and grades your agents.
  • Revelir does the same, on 100% of your conversations.
  • Revelir gives you the reasoning, the quote it came from, and the document it checked against.
app.revelir.ai / evaluations / ticket-view

Incorrect Charge - Wrong Amount Charged

#DEMO-51B5FE33 · Agent: Michael Chen · Graded automatically Aug 2, 2026

Score

40 / 100

Status

✦ Assessed by AI

Conversation

Customer · 9:42 AM

I was just charged for $55.99 for a subscription I cancelled last month! This is outrageous. I want this fixed immediately.

Michael Chen · 9:44 AM

Welcome to Revelir! I'm Michael Chen, happy to help you today. I understand you're upset about an incorrect charge of $55.99 for a subscription you believe was cancelled. I can definitely look into this for you.

Customer · 9:45 AM

Yes, that's right. I cancelled it weeks ago. You guys are thieves!

Michael Chen · 9:47 AM

I can see how frustrating that must be, Ahmed. To help me investigate this specific charge, could you please provide the transaction ID or reference number for the $55.99 payment?

Customer · 9:48 AM

Why should I have to do your job for you? Just find it! It's REF-789012.

Michael Chen · 9:50 AM

Thank you for providing the reference number, REF-789012. It looks like this charge is related to a recurring service that, according to our system, was not fully cancelled before the billing cycle. I need to raise a ticket to our L2 support team to review the cancellation request details and see if we can process a refund.

Customer · 9:52 AM

L2 support? What is that? This is unacceptable. I already told you I cancelled it. Just give me my money back!

QA scorecard · 10 metrics

Open any failed metric to see the evidence behind it.

The problem

Two agents, same policy. Two different answers.

Both were trained on the same refund policy. In your dashboard both tickets look the same: resolved, on time, no complaint attached.

Adam
Handle time 4 min

Says the booking is not refundable, politely, and closes the ticket. The policy said it was refundable.

Chargeback, three weeks later
Hannah
Handle time 9 min

Checks the policy, confirms the refund, and explains when the money will arrive.

Customer books again

2 to 5%

of conversations get reviewed by a human. That is the manual QA industry standard. Everything grey went out unchecked.

Adam's ticket was one of the grey squares. Nobody reviewed it, and nobody knew until the customer disputed the charge.

How it works

What happens to a ticket once your agent closes it.

Our team does the setup with you.

01

Connect your helpdesk

Tickets flow into Revelir automatically as they close.

02

We read your documents

Your SOPs, refund rules, escalation paths and knowledge base, so Revelir knows what the correct answer should have been.

03

We configure your scorecard

The QA scorecard your team already uses, metric by metric, with your own definitions.

04

We calibrate against your team

Your QA team grades a set by hand. We compare, adjust, and keep going until Revelir matches their judgement. You see the agreement rate for yourself.

Grading 20,000 conversations only helps if someone tells Adam.

With 30 agents and tens of thousands of tickets a month, no team lead can give that feedback daily. Every agent gets their own coach, built from their own graded conversations.

  • A daily focus drawn from their own tickets, naming the metric they missed and quoting the exchange
  • One action for the day, with repeat gaps flagged as persistent
  • It answers questions. An agent can ask why they were marked down and get an answer from their own QA history
The Personal Coach view in RevelirQA

Teams running QA on all of it.

Rendy D.tiket.com

We've manually reviewed tickets for years. Revelir is the first product that has made AI ticket review at scale actually usable.

Lorens H.xendit.co

The team is incredibly responsive. Feedback turns into shipped features fast, it genuinely feels like we're building the product together.

~90%agreement with human QA assessments
100%of conversations graded, every day
Minutesfrom a conversation closing to a graded result

Who this is for

Is this you?

  • Quality varies by agent and you cannot see where or why
  • 30 or more customer service agents
  • 5,000 or more conversations a month
  • QA is manual, or the QA team is too small for the volume

The things people ask first.

Do we have to change our QA scorecard?

No. Revelir is configured against the scorecard your team already uses, metric by metric, with your own definitions. Our team does that configuration for you.

What happens when the AI gets a grade wrong?

Your QA lead sees the reasoning, the quote it came from, and the document it was checked against, then overrides the grade. Those overrides are how we calibrate, so disagreement is the useful part.

How accurate is it?

Around 90% agreement with human QA assessments today. You see the agreement rate on your own conversations during the pilot, before committing to anything.

How is this different from the QA tool in our helpdesk?

Helpdesk QA tools give your analysts a form to fill in, so coverage is still limited by how many tickets a person can read. Revelir does the grading itself, on all of them, and checks answers against your own policy documents.

Which helpdesks do you connect to?

We integrate through the APIs of all major helpdesks, Zendesk and Salesforce included. If your team runs on something else, tell us on the call and we will confirm it before any pilot starts.

How long does setup take?

A pilot on your own tickets runs in days. Most of that time is us reading your documents and calibrating against your graders.

Where does our conversation data go?

Data is processed in our cloud environment and is never used to train third-party models. Full sub-processor list and security documentation available on request.

Run a pilot on your own tickets.

Thirty minutes to walk through how your team grades conversations today. Then we grade a set of your own, and show you where Revelir agreed with your QA team and where it did not.

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